A Model for Urban Environment Instance Segmentation with Data Fusion

• Published in: Sensors (Basel, Switzerland) Vol. 23; no. 13; p. 6141
• Main Authors: Du, Kaiyue, Meng, Jin, Meng, Xin, Wang, Shifeng, Yang, Jinhua
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 04.07.2023; MDPI
• Subjects: Accuracy; Algorithms; Analysis; Annotations; Autonomous vehicles; Cameras; Classification; data fusion; Deep learning; Design; Driverless cars; environment perception; instance segmentation; Markov Random Field; mean shift; Neural networks; Optical radar; Remote sensing; Semantics; Sensors; Support Vector Machines; data fusion; instance segmentation; environment perception; Markov Random Field; mean shift; Support Vector Machines

Fine-grained urban environment instance segmentation is a fundamental and important task in the field of environment perception for autonomous vehicles. To address this goal, a model was designed with LiDAR pointcloud data and camera image data as the subject of study, and the reliability of the mod...